In the field of e-commerce, there exists a demand for businesses to be able to tailor their products and services to better match the needs and requirements of their customers. This demand exists equally in both the business-to-business (B2B) and the business-to-consumer (B2C) worlds. A particular example of such tailoring of business services is in the field of personalization. Personalization allows a business to personalize, or otherwise customize, their offerings to a particular customer, or group of customers. For example, in an Internet/Web environment, a B2C content provider may wish to deploy a Web site in which the Web site content is personalized for each individual customer visiting the site, or for each type of customer based on certain characteristics. Examples of such Web-based B2C providers include on-line catalog-providers; product vendors; news, media and entertainment providers; and information or reference sources.
As their business success has come to depend more and more on dependable personalized services, e-commerce providers have demanded more from their personalization systems. A prevalent demand is for personalization systems that can assist a provider in not only providing a personalized Web site, but can allow the e-commerce provider to tailor all of their business functions—marketing, production, distribution, etc. at a single source, and to update the information or data that these functions rely on, in a quick, dependable, and easily-modifiable manner, that requires little or no system down-time.
Traditional systems used for personalizing web content are mostly analytic in nature, and rely on using previously collected data in a manner that allows an administrator to modify a web site or e-commerce application based on an understanding of that data. For example, personalization systems from vendors such as ATG and Broadbase, who primarily provide Online Analytical Processing (OLAP) systems, rely on the commerce provider collecting sufficient by large amounts of data to represent their target population in an analytical way, i.e. statistically, and to then use that data to personalize content to a sub section of the population. Data can be collected by traditional mechanisms, i.e. through standard market research tools, or can be collected on-line through for example, maintaining histories of a customer's prior use. However, such data is typically stored in a repository for further analysis before it is subsequently analyzed and used to allow an administrator to update the actual content. In this manner the data is not used to provide a real-time personalization of the system, or one that is easily modifiable in run-time by an administrator. Instead, the data is used more to present a change in content over a large period of time and a large number of users. No attempt is made to customize data content at the per-user level during the actual user or customer session.
As today's e-commerce demands grow to requiring real-time update of personalized user content, and/or available products and services, there is an ever increasing demand for systems that allow an administrator to quickly customize the content that is presented to a user during application run-time, and even when the user is actively operating within a session. Furthermore, systems that allow this change to be effected automatically, i.e. by using rules or some other mechanism to alter the content presented to a user during their session, are especially useful. As end users become more sophisticated, and demand better quality of service from their content providers, and as back-end commerce applications become more complex, and flexible enough to offer such a detailed variation in content, there is an ever increasing demand for systems that allow or support the ability to provide real-time personalized data content to the user. Systems that can do this, while at the same time allowing great ease of use in setting up data content and marketing campaigns, are especially useful, since they allow an administrator to quickly administer the actual content and the rules by which that content will be sent to the user.